Mobile robots, including Automated Guided Vehicles (AGVS), are becoming more and more common in society. Mobile robots are widely used in industry, military and security environments. They also appear as consumer products, such as, but not limited to, for entertainment, as toy robots for instance, or to perform certain tasks like vacuum cleaning for instance.
Localization techniques refer to processes by which an Automated Guided Vehicles and mobile robots robot determines its position with respect to its surroundings in the workspace. This is an essential component for path planning to specific locations and for preventing the robot from reaching undesired locations.
While Global Positioning Systems (GPS) provide comfortable solutions for outdoor localization, other methods have to be considered for indoor localization.
One of the methods to perform indoor localization is to put landmarks at known locations and measure their bearings with respect to the robot during robot operation.
The traditional geometric method for localization from landmark bearings is based on the idea that two bearing measurements enforce the position of the robot to lie on a defined circle.
Thus, according to various investigators among them are M. Betke, and L. Gurvits “Mobile robot Localization using landmarks” in IEEE Trans. Robot. Automat., Vol. 13, number 2, pages 251-263, 1997, when three measurements are available the robot location can be computed.
The problem associated with this method is that it does not scale up for more than three measurements.
To overcome this problem, I. Shimshoni “On Mobile Robot Localization from Landmark Bearings” in IEEE Trans. Robotics and Automation volume 18 number 3, pages 971-976, 2002 suggested an efficient algebraic technique which allows estimating the error when more than three measurements are available.
Such algebraic technique deals correctly with unbiased noise and yields close to optimal results. However, in real world situations other sources of errors are present and must be handled by a localization method.
Thus, since mobile robot systems are widely used, an aim of the present invention is to disclose a localization method which enables handling a wide range of error sources reliably and efficiently.
Other advantages and aims of the present invention will become apparent after reading the present invention and reviewing the accompanying figures.